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首页> 外文期刊>International journal of advanced intelligence paradigms >TaskTracker aware scheduler with resource availability control for Hadoop MapReduce
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TaskTracker aware scheduler with resource availability control for Hadoop MapReduce

机译:TaskTracker意识到Hadoop MapReduce的资源可用性控件的调度程序

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摘要

Schedulers are playing a vital role in task assignment for Hadoop MapReduce. In some scenario, the default schedulers of Hadoop spawn tasks in TaskTracker without checking the external dependency and may fail. As a result, Hadoop should rerun the tasks in another TaskTracker. To address this issue, TaskTracker aware scheduler has been introduced. This paper focuses the resource availability control of TaskTracker aware scheduler. The proposed scheduler will not allow a task to run and fail if the load of the TaskTracker reaches its threshold for the Job. The performance of this scheduler may increase if the scheduler is aware of the status of the resources present in the TaskTracker nodes. The main features of this scheduler are user controllability of jobs and configuration based resource utilisation control for task allocation.
机译:调度程序在Hadoop MapReduce的任务分配中扮演了一个重要的作用。在某些情况下,TaskTracker中Hadoop Spawn任务的默认调度程序在不检查外部依赖项的情况下,可能会失败。因此,Hadoop应该重新运行另一个TaskTracker中的任务。要解决此问题,还介绍了TaskTracker意识到调度程序。本文重点是TaskTracker感知计划程序的资源可用性控制。如果TaskTracker的负载达到作业的阈值,则建议的调度程序不会允许运行并失败。如果调度器知道任务触发器节点中存在的资源的状态,则该调度器的性能可能会增加。该调度程序的主要特征是对任务分配的基于作业和配置的资源利用控制的用户可控性。

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